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        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411
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        About MultiQC

        This report was generated using MultiQC, version 1.27

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/MultiQC/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2025-01-27, 00:42 IST based on data in: /lustre1/home/mass/eskalon/Porites/analysis/trimming/sortmerna/output/logs

        General Statistics

        Showing 31/31 rows.
        Sample NamerRNA
        4-MF10-4a_trim_2P
        58.4%
        23-MF10-1a_trim_2P
        31.9%
        25-CC40-2b_trim_2P
        3.1%
        27-MF40-2b_trim_2P
        54.5%
        28-CC10-9b_trim_2P
        57.0%
        31-MF40-5b_trim_2P
        83.6%
        32-CC10-1b_trim_2P
        86.6%
        35-MF40-1b_trim_2P
        45.4%
        37-CC40-8b_trim_2P
        71.0%
        42-MF10-10b_trim_2P
        21.1%
        48-CC10-6b_trim_2P
        86.7%
        49-CC40-1b_trim_2P
        62.3%
        63-MF-SS-60_trim_2P
        19.2%
        66-MF-DS-52_trim_2P
        79.4%
        73-CC-SS-38_trim_2P
        79.4%
        75-CC-DD-84_trim_2P
        20.9%
        78-MF-DS-54_trim_2P
        62.4%
        80-1-CC-DS-86_trim_2P
        2.2%
        81-CC-DS-87_trim_2P
        51.8%
        84-CC-DD-80_trim_2P
        71.8%
        91-CC-DS-89_trim_2P
        87.1%
        94-CC-SS-37_trim_2P
        73.5%
        97-MF-SS-64_trim_2P
        40.3%
        98-MF-SS-69_trim_2P
        64.1%
        99-MF-SD-43_trim_2P
        2.0%
        100-CC-SD-73_trim_2P
        42.2%
        102-CC-DD-82_trim_2P
        38.1%
        108-CC-DD-94_trim_2P
        67.9%
        114-MF-SD-45_trim_2P
        14.0%
        117-MF-SD-44_trim_2P
        4.6%
        123-CC-DD-81_trim_2P
        3.1%

        SortMeRNA

        Program for filtering, mapping and OTU-picking NGS reads in metatranscriptomic and metagenomic data.URL: http://bioinfo.lifl.fr/RNA/sortmernaDOI: 10.1093/bioinformatics/bts611

        The core algorithm is based on approximate seeds and allows for fast and sensitive analyses of nucleotide sequences. The main application of SortMeRNA is filtering ribosomal RNA from metatranscriptomic data.

        Created with MultiQC

        MultiQC v1.27 - Written by Phil Ewels, available on GitHub.

        This report uses Plotly, jQuery, jQuery UI, Bootstrap and FileSaver.js.